# What is Quantum Machine Learning, and is it a Thing?

** #ML4ALL ** | ** 30 April 2019 **

Sarah Kaiser

@crazy4pi314

Pensar Development

#### Data model for quantum computers

### Quantum + bits = QUBITS!

To represent the state of $n$ qubits, we use a complex valued vector $2^n$ elements long, called a *ket*.

$$|x_{n}\rangle = \begin{bmatrix} \alpha_{1}\\ \alpha_{2}\\ \alpha_{3}\\ ...\\ \alpha_{2^n}\end{bmatrix}$$
#### Example: 2 qubit register

To represent the state of 2 qubits, we use a complex valued vector $2^2 = 4$ elements long.

$$|ðŸ’–\rangle = \begin{bmatrix} 0\\ \frac{1}{\sqrt{2}}\\ \frac{-i}{\sqrt{2}} \\ 0 \end{bmatrix}$$
## TL;DR on quantum computing

Quantum computers are **not universally** faster or more powerful. Think like GPUs!

The applications that are exciting in the near term are not necessarily the ones hyped.

We can start **today** programming and playing around with early hardware and simulators!

### Quantum Neural Nets

- We can train restricted Boltzmann machines faster on a quantum computer

- Encoding the problem in qubits is a problem, need qRAM to make useful

*For more look here: Quantum Machine Learning*
## Takeaways:

Keep it real* when reading about quantum computing ðŸ˜Ž

Quantum resources necessitate changing how we think about algorithms

Quantum machine learning is exciting, but very alpha

More on QML from Quantum Model Zoo